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SU-E-J-178: Development of Image Planning System for Radiation Therapy
Medical Physics
|May 19, 2017
Summary
A new patient-specific imaging system optimizes radiotherapy imaging parameters for better image quality. This system predicts optimal settings based on dose and imaging goals, improving diagnostic accuracy in image-guided radiotherapy.
Area of Science:
- Medical Physics
- Radiotherapy
- Medical Imaging
Background:
- Radiotherapy imaging dose constraints differ from diagnostic imaging.
- Current imaging parameter selection relies on broad patient and imaging categories.
- Optimizing imaging parameters can improve image quality and therapeutic outcomes.
Purpose of the Study:
- To develop and benchmark a patient-specific image planning system.
- To predetermine optimal imaging acquisition parameters for image-guided radiotherapy.
- To balance patient dose with desired image quality.
Main Methods:
- Developed a Matlab algorithm for divergent ray-tracing through CT data.
- Calculated energy-specific attenuation and integrated measured detector response.
- Validated the system using a flat panel imager, linear accelerator, and lung phantom.
Main Results:
- Qualitative agreement observed between simulated and measured images.
- The algorithm predicts detector under-exposure and saturation at various beam qualities and exposures.
- Object detectability decreased predictably with increasing exposure levels (mAs).
Conclusions:
- Established the feasibility of a patient-specific image planning system.
- Demonstrated qualitative accuracy in predicting image quality and object detectability.
- Further work will incorporate beam heterogeneity for quantitative accuracy.
